HMMSTR 20120205 – Protein Secondary Structure Prediction

HMMSTR 20120205

:: DESCRIPTION

HMMSTR ( Hidden Markov Model for Local Sequence-Structur) is a hidden Markov model for protein structure prediction. The program takes as input an amino acid probability distribution (or profile) for each residue position.  A profile may be derived from a multiple sequence alignment, or by running the database search program such as PSI_BLAST. It contains the programs needed to predict secondary structure starting with a sequence profile. The sequence profile (a vector of 20 probabilities for each residue in the sequence) can be the output of a profile HMM such as HMMer. It may also be the output of Psi-Blast, which uses profiles internally, or may be generated from a multiple sequence alignment. The programs in this package, HMMSTR and associated format converters, will give you a probabilistic prediction of each of the six DSSP symbols: H,E,G,S,T and _. For now, this is a bare-bones package.

HMMSTR Online Version

::DEVELOPER

Chris Bystroff

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

HMMSTR

:: MORE INFORMATION

Citaiton

BMC Bioinformatics. 2008 Oct 10;9:429. doi: 10.1186/1471-2105-9-429.
Pairwise covariance adds little to secondary structure prediction but improves the prediction of non-canonical local structure.
Bystroff C, Webb-Robertson BJ.

Bystroff C, Thorsson V & Baker D. (2000).
HMMSTR: A hidden markov model for local sequence-structure correlations in proteins.
Journal of Molecular Biology 301, 173-90.

RNAsc – RNA Secondary Structure Prediction using SHAPE or inline-probing data

RNAsc

:: DESCRIPTION

RNAsc is a web server that computes RNA secondary structure with user-input chemical/enzymatic probing data, especially Selective 2′-hydroxyl acylation analyzed by primer extension (SHAPE) or inline-probing data

::DEVELOPER

Clote Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 RNAsc

:: MORE INFORMATION

Citation:

PLoS One. 2012;7(10):e45160. doi: 10.1371/journal.pone.0045160. Epub 2012 Oct 16.
Integrating chemical footprinting data into RNA secondary structure prediction.
Zarringhalam K1, Meyer MM, Dotu I, Chuang JH, Clote P.

transFold – Super-secondary Structure Prediction of Transmembrane β-barrel proteins

transFold

:: DESCRIPTION

transFold is a web server for beta-barrel supersecondary structure prediction. Unlike other software which employ machine learning methods, transFold uses multi-tape S-attribute grammars to describe the space of all possible supersecondary structures, then applies dynamic programming to compute the global energy minimum structure.

::DEVELOPER

Clote Lab 

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

J. Waldispühl, B. Berger, P. Clote, J.-M. Steyaert,
TransFold: a Web Server for predicting the structure and residue contacts of transmembrane beta-barrels,
Nucleic Acids Res. 34(Web Server Issue):189-193 (2006).

RNAbor – Compute Structural Neighbors of an RNA Secondary Structure

RNAbor

:: DESCRIPTION

RNAbor is a web server to compute secondary structural neighbors of a given RNA structure.

::DEVELOPER

Clote Lab 

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

E. Freyhult, V. Moulton, P. Clote.
RNAbor: A web server for RNA structural neighbors.
Nucleic Acids Res. 2007 Jul 1;35(Web Server issue):W305-9. Epub 2007 May 25.

Emap2sec – Protein secondary structure detection in intermediate-resolution cryo-EM maps

Emap2sec

:: DESCRIPTION

Emap2sec is a deep learning-based tool for detecting protein secondary structures from intermediate resolution cryo-EM maps.

::DEVELOPER

Kihara Bioinformatics Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

Emap2sec

:: MORE INFORMATION

Citation

Nat Methods. 2019 Sep;16(9):911-917. doi: 10.1038/s41592-019-0500-1. Epub 2019 Jul 29.
Protein secondary structure detection in intermediate-resolution cryo-EM maps using deep learning.
Maddhuri Venkata Subramaniya SR, Terashi G, Kihara D.

CROSS / CROSSalign / CROSSalive – Recognition of RNA Secondary Structure

CROSS / CROSSalign / CROSSalive

:: DESCRIPTION

CROSS predicts the secondary structure propensity profile of an RNA molecule at single-nucleotide resolution. CROSS produces a table with the propensity scores and a graphical representation of the profile.

CROSSalign computes the similarity of RNA secondary structure

CROSSalive computes the structure of RNA molecules in vivo. Changes of structure upon N6-Methyladenosine methylation can be predicted.

::DEVELOPER

Tartaglia Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

CROSSalive: a web server for predicting the in vivo structure of RNA molecules.
Delli Ponti R, Armaos A, Vandelli A, Tartaglia GG.
Bioinformatics. 2019 Aug 28. pii: btz666. doi: 10.1093/bioinformatics/btz666.

Front Mol Biosci. 2018 Dec 3;5:111. doi: 10.3389/fmolb.2018.00111. eCollection 2018.
A Method for RNA Structure Prediction Shows Evidence for Structure in lncRNAs.
Delli Ponti R, Armaos A, Marti S, Tartaglia GG

A high-throughput approach to profile RNA structure.
Delli Ponti R, Marti S, Armaos A, Tartaglia GG.
Nucleic Acids Res. 2017 Mar 17;45(5):e35. doi: 10.1093/nar/gkw1094.

comRNA 1.80 – Common RNA Secondary Structure Predictor

comRNA 1.80

:: DESCRIPTION

comRNA is a new program that predicts common RNA secondary structure motifs in a group of related sequences.The algorithm applies graph-theoretical approaches to automatically detect common RNA secondary structure motifs in a group of functionally or evolutionarily related RNA sequences.

::DEVELOPER

Stormo Lab in Department of Genetics, Washington University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

comRNA

:: MORE INFORMATION

Citation:

Yongmei Ji, Xing Xu and Gary D. Stormo,
A graph theoretical approach for predicting common RNA secondary structure motifs including pseudoknots in unaligned sequences
, Bioinformatics, 2004 Jul 10; 20(10):1591-1602.”

AlphaPred – Prediction of Alpha-turns in Proteins using Multiple Alignment and Secondary Structure Information

AlphaPred

:: DESCRIPTION

The AlphaPred server predicts the alpha turn residues in the given protein sequence. The method is based on the neural network training on PSI-BLAST generated position specific matrices and PSIPRED predicted secondary structure.

::DEVELOPER

Dr. G P S Raghava

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

Kaur H & Raghava GP. (2004).
Prediction of alpha-turns in proteins using PSI-BLAST profiles and secondary structure information.
Proteins. 55: 83-90

GammaPred – Prediction of Gamma-turns in Proteins using Multiple Alignment and Secondary Structure Information

GammaPred

:: DESCRIPTION

The GammaPred server predicts the gamma turn residues in the given protein sequence. The method is based on the neural network training on PSI-BLAST generated position specific matrices and PSIPRED predicted secondary structure. Two neural networks with a single hidden layer have been used where the first sequence-to-structure network is trained on PSI-BLAST obtained position specific matrices. The filtering has been done by second structure-to-structure network trained on output of first net and PSIPRED predicted secondary structure. The training has been carried out using error backpropagation with a sum of square error function(SSE).

::DEVELOPER

Dr. G P S Raghava

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

Kaur, H. and Raghava, G.P.S. (2003)
A neural network based method for prediction of gamma-turns in proteins from multiple sequence alignment.
Protein Science 12: 923-929.

APSSP2 – Advanced Protein Secondary Structure Prediction Server

APSSP2

:: DESCRIPTION

APSSP2 allows to predict the secondary structure of protein’s from their amino acid sequence.

::DEVELOPER

Dr. G P S Raghava

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

Raghava, G. P. S. (2002)
APSSP2 : A combination method for protein secondary structure prediction based on neural network and example based learning.
CASP5. A-132.